An efficient energy management of a hybrid electric vehicle using hybrid QNN-GOA technique

This manuscript proposes a hybrid technique for energy management of a series of hybrid electric tracked vehicles (SHETV). The proposed hybrid technique isthe gannet optimization algorithm (GOA) and Quantum Neural Network (QNN) and commonly it is called as QNN- GOA technique. The proposed technique's primary goal is to increase the fuel economy and the operation efficiency of the hybrid electric vehicle (HEV). The SHETV powertrain model is built before the matching energy management formulation is developed. The Quantum Neural Networks (QNNs) arethen employed for predicting the optimal value of the system. Additionally, the Gannet Optimization Algorithm (GOA) isdeveloped for energy management control in the SHETV. By then, the proposed technique is done in the MATLAB platform and the execution is computed with the existing procedures. From the outcome, it concludes that the proposedtechniquebased SOC is high compared to existing techniques.